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Learning outcomes
Discuss the role of search algorithms and constraint satisfaction problems (CSPs) in solving real-world problems: Understand and articulate how search techniques and CSP methodologies can be applied to find solutions in various domains.
Explain the theoretical foundations of search and CSP techniques, focusing on problem-solving using knowledge and reasoning: Delve into the principles and theories that underpin search algorithms and CSPs, with an emphasis on knowledge-based problem-solving.
Evaluate AI systems, particularly graph databases, logical reasoning, and probabilistic models, for their suitability in specific applications and domains: Develop the ability to critically assess the effectiveness of graph databases, logic-based systems, and probabilistic models in diverse real-world contexts.
Describe/discuss generative AI and its applications and analyse the social implications of AI: Explore the latest advancements in generative AI, its practical uses, and the ethical considerations and societal impacts of AI technologies.